Much of computer science involves designing completely automatic systems that will later solve some specific problem -- systems to accept input data and, in a reasonable amount of time, calculate the correct response or a correct-enough approximation.
In addition, people in computer science spend a surprisingly large amount of human time finding and fixing problems in their programs -- debugging.
Well-defined problems allow for more initial planning than ill-defined problems.
Solving problems sometimes involves dealing with pragmatics, the way that context contributes to meaning, and semantics, the interpretation of the problem.
Problem solving in psychology refers to the process of finding solutions to problems encountered in life.
Solutions to these problems are usually situation- or context-specific.However, already in 1958, John Mc Carthy proposed the advice taker, to represent information in formal logic and to derive answers to questions using automated theorem-proving.A important step in this direction was made by Cordell Green in 1969, using a resolution theorem prover for question-answering and for such other applications in artificial intelligence as robot planning.One such component is the emotional valence of "real-world" problems and it can either impede or aid problem-solving performance.Researchers have focused on the role of emotions in problem solving , In conceptualization, human problem solving consists of two related processes: problem orientation and the motivational/attitudinal/affective approach to problematic situations and problem-solving skills.Mental health professionals study the human problem solving processes using methods such as introspection, behaviorism, simulation, computer modeling, and experiment.Social psychologists look into the person-environment relationship aspect of the problem and independent and interdependent problem-solving methods.There are two different types of problems, ill-defined and well-defined: different approaches are used for each.Well-defined problems have specific goals and clear expected solutions, while ill-defined problems do not.It can also be applied to a product or process prior to an actual failure event—when a potential problem can be predicted and analyzed, and mitigation applied so the problem never occurs.Techniques such as failure mode and effects analysis can be used to proactively reduce the likelihood of problems occurring.